2022-04-19 15:37:20 +00:00
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import torch
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import fvcore.nn
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import fvcore.common
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from fvcore.nn import FlopCountAnalysis
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from classification_ScanObjectNN.models import pointMLPElite
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model = pointMLPElite()
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2022-04-19 19:45:58 +00:00
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model.eval()
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2022-04-19 15:37:20 +00:00
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# model = deit_tiny_patch16_224()
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2022-04-19 19:45:58 +00:00
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inputs = (torch.randn((1,3,1024)))
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2022-04-19 15:37:20 +00:00
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k = 1024.0
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flops = FlopCountAnalysis(model, inputs).total()
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print(f"Flops : {flops}")
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flops = flops/(k**3)
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print(f"Flops : {flops:.1f}G")
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params = fvcore.nn.parameter_count(model)[""]
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print(f"Params : {params}")
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params = params/(k**2)
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print(f"Params : {params:.1f}M")
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